| Download | - View accepted manuscript: Attribute Value Reordering for Efficient Hybrid OLAP (PDF, 268 KiB)
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| Author | Search for: Kaser, O.; Search for: Lemire, Daniel |
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| Format | Text, Article |
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| Conference | The Sixth International Workshop on Data Warehousing and OLAP (DOLAP'03), November 7, 2003, New Orleans, Louisiana, USA |
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| Subject | data cubes; normalization; chunking; multidimensional binary arrays; OLAP; MOLAP |
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| Abstract | The normalization of a data cube is the process of choosing an ordering for the attribute values, and the chosen ordering will affect the physical storage of the cube's data. For large multidimensional arrays, proper normalization can lead to more efficient storage in hybrid OLAP contexts that store dense and sparse chunks differently. We show that it is NP-hard to compute an optimal normalization even for 1×3 chunks, although we find an exact algorithm for 1×2 chunks. When attributes are nearly statistically independent, we show that an optimal normalization is given by dimension-wise attribute frequency sorting, which can be done in time O(<em>dn</em>log(<em>n</em>)) for data cubes of size <em>n<sup>d</sup></em> . When attributes are not independent, we propose and evaluate a number of heuristics.Our optimized hybrid OLAP storage mechanism was observed to be 44% more storage efficient than ROLAP and the gains due to normalization alone accounted for 45% of this increase in efficiency. |
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| Publication date | 2003 |
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| In | |
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| Language | English |
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| NRC number | NRCC 46510 |
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| NPARC number | 5765320 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 5de58bb0-1836-41b1-9308-d2d95b0435a2 |
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| Record created | 2009-03-29 |
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| Record modified | 2021-01-05 |
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